Dissertation/Thesis Abstract

Error Reduction Using Kalman Filters
by Sondh, Sidhartha, M.S., California State University, Long Beach, 2018, 59; 10784214
Abstract (Summary)

Error Reduction using Kalman Filters (KF) will remove the various positional errors that arise from onboard inertial sensors housed within the Inertial Navigation System (INS), as well as GPS signals that get distorted via the earth’s atmosphere. The paper will show that the KF reduces both the process and measurement noises to recursively reduce the error introduced into the system to deliver a best estimate as to the positioning of a defined object. The KF in the context of this paper is used to improve the tracking of a satellite from a ground station, although the concept of using a KF can be used in various object tracking schemes. The paper will discuss software based approach to removing GPS signal multipath errors to show that errors can be reduced electronically.

Indexing (document details)
Advisor: Yeh, Hen-Geul Henry
Commitee: Ahmed, Aftab, Wang, Fei
School: California State University, Long Beach
Department: Electrical Engineering
School Location: United States -- California
Source: MAI 58/01M(E), Masters Abstracts International
Subjects: Electrical engineering
Keywords: Itirative, KF, Kalman filters
Publication Number: 10784214
ISBN: 978-0-438-19623-0
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